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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning

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Computer Vision and Machine Learning with RGB-D Sensors (Hardcover, 2014 ed.) Loot Price: R2,892
Discovery Miles 28 920
Computer Vision and Machine Learning with RGB-D Sensors (Hardcover, 2014 ed.): Ling Shao, Jungong Han, Pushmeet Kohli, Zhengyou...

Computer Vision and Machine Learning with RGB-D Sensors (Hardcover, 2014 ed.)

Ling Shao, Jungong Han, Pushmeet Kohli, Zhengyou Zhang

Series: Advances in Computer Vision and Pattern Recognition

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Loot Price R2,892 Discovery Miles 28 920 | Repayment Terms: R271 pm x 12*

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The combination of high-resolution visual and depth sensing, supported by machine learning, opens up new opportunities to solve real-world problems in computer vision.

This authoritative text/reference presents an interdisciplinary selection of important, cutting-edge research on RGB-D based computer vision. Divided into four sections, the book opens with a detailed survey of the field, followed by a focused examination of RGB-D based 3D reconstruction, mapping and synthesis. The work continues with a section devoted to novel techniques that employ depth data for object detection, segmentation and tracking, and concludes with examples of accurate human action interpretation aided by depth sensors.

Topics and features: discusses the calibration of color and depth cameras, the reduction of noise on depth maps, and methods for capturing human performance in 3D; reviews a selection of applications which use RGB-D information to reconstruct human figures, evaluate energy consumption, and obtain accurate action classification; presents an innovative approach for 3D object retrieval, and for the reconstruction of gas flow from multiple Kinect cameras; describes an RGB-D computer vision system designed to assist the visually impaired, and another for smart-environment sensing to assist elderly and disabled people; examines the effective features that characterize static hand poses, and introduces a unified framework to enforce both temporal and spatial constraints for hand parsing; proposes a new classifier architecture for real-time hand pose recognition, and a novel hand segmentation and gesture recognition system.

Researchers and practitioners working in computer vision, HCI and machine learning will find this to be a must-read text. The book also serves as a useful reference for graduate students studying computer vision, pattern recognition or multimedia.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: Advances in Computer Vision and Pattern Recognition
Release date: July 2014
First published: 2014
Editors: Ling Shao • Jungong Han • Pushmeet Kohli • Zhengyou Zhang
Dimensions: 235 x 155 x 24mm (L x W x T)
Format: Hardcover
Pages: 316
Edition: 2014 ed.
ISBN-13: 978-3-319-08650-7
Categories: Books > Computing & IT > Social & legal aspects of computing > Human-computer interaction
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision
Books > Computing & IT > Applications of computing > Image processing > General
LSN: 3-319-08650-2
Barcode: 9783319086507

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